Model based object finding in occluded cluttered environments
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
The aim of the thesis is object finding in occluded and cluttered environment using computer vision techniques and robot motion. Difficulties of the object finding are 1. finding objects at hidden area and 2. finding unrecognized objects. For solving the difficulties, two methods were developed, one is for finding objects in occluded cluttered environments using model based object finding and the other to increase the robustness in object finding by identifying known objects that are unidentified. The goal was to search occluded areas with the bumblebee2 stereo camera to be able to identify all known objects in the environment by removing all visible known objects To identify known objects SURF  was used and to be able to remove the identified objects their location first needed to be localized. To localize the object‘s x and y coordinate the information from SURF  was used, and the distance coordinate z is calculated using the depth image from the stereo camera. The method to identify objects the SURF  algorithm had missed to identify uses a method to find unknown segments in the environment. By using a push motion on the segments to change their angle it can remove possible light reflections and the object can be identified. The results of this research show that the method can find objects in occluded cluttered areas and it can also identified missed known objects.
Place, publisher, year, edition, pages
, UMNAD, 846
IdentifiersURN: urn:nbn:se:umu:diva-36524OAI: oai:DiVA.org:umu-36524DiVA: diva2:354609